Fiber reinforced plastics are gaining importance for their weight saving potential due to the influence of sociopolitical topics such as energy efficiency and conservation of resources. Long fibers and short fibers are increasingly used for structural components. The high requirements on the performance in automotive, aerospace and also the sports and leisure sector demand a full exploitation of these materials´ potential. For optimization a precise understanding of the processing effects is inevitable. In this work two different testing parts were produced in a single-stage direct processing on an injection molding compounder and tested for their respective resulting fiber properties. Hardly any significant influence of the process parameters on the mechanical properties was found. However, increasing fiber length at the end of the cavity could be observed as well as an influence of increasing fiber concentration on a significantly lowered fiber length. The latter can be assigned to higher fiber-fiber interaction. An influence of a change in wall thickness on the fiber length reduction could only be determined for low fiber contents. For higher fiber contents the fiber length degradation is dominated by fiber-fiber interaction.
Short fiber reinforced thermoplastics (SFT) are extensively used due to their excellent mechanical properties and low processing costs. Long fiber reinforced thermoplastics (LFT) show an even more interesting property profile and are increasingly used for structural parts. However, their processing by injection molding is not as simple as for SFT, and their anisotropic properties resulting from the fiber microstructure (fiber orientation, length, and concentration) pose a challenge with regard to the engineering design process. To reliably predict the structural mechanical properties of fiber reinforced thermoplastics by means of micromechanical models, it is also necessary to reliable predict the fiber microstructure. Therefore, it is crucial to calibrate the underlying prediction models, such as the fiber orientation model, within the process simulation. In general, these models may be adjusted manually, but this is usually ineffective and time-consuming. To overcome this challenge, a new calibration method was developed to automatically calibrate the fiber orientation model parameters of the injection molding simulation by means of optimization methods. This optimization routine is based on experimentally determined fiber orientation distributions and leads to optimized parameters for the fiber orientation prediction model within a few minutes. To better understand the influence of the model parameters, different versions of the fiber orientation model, as well as process and material influences on the resulting fiber orientation distribution, were investigated. Finally, the developed approach to calibrate the fiber orientation model was compared with a classical approach, a direct optimization of the whole process simulation. Thereby, the new optimization approach shows a calculation time reduced by the factor 15 with comparable error variance.
In this work, we assessed the impact of post-quantum (PQ) cryptography on public key infrastructure (PKI). First, we modified a commercially available certification authority (CA) to issue 'hybrid' certificates (X.509 certificates with PQ extensions). Then we assessed the impact of using these certificates on some existing protocols, including TLS, OCSP, CMP, and EST, with open-source libraries OpenSSL and CFSSL, and with a commercially available cryptographic toolkit. We found that most of the protocols and libraries we tested worked with hybrid certificates, and some of the failures could be overcome with minor modifications to the existing software. Our work differentiates from and extends previous work by focusing on the impact of PQ algorithms on certificate issuance, revocation, and management protocols, which are necessary for enterprises to manage PKI in their environments. The impact on TLS is also investigated, allowing consistency with previous results to be evaluated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.